Can we detect the development of baroreflex sensitivity in humans between 11 and 20 years of age?
Bibliographic record
Abstract
The aim of the study was to determine changes of baroreflex sensitivity in humans between 11 and 20 years of age. Continuous 5 min blood pressure recordings using a Finapres were taken in 415 healthy subjects while in a sitting, resting position (breathing at a frequency of 0.33 Hz). Beat-by-beat values of interbeat intervals (IBI) or heart rate, and systolic and diastolic blood pressures were measured. Baroreflex sensitivity in ms/mmHg (BRS) and in mHz/mmHg (BRSf) was determined at an average frequency of 0.1 Hz by spectral analysis. BRS did not correlate with age, but BRSf significantly decreased with age (p < 0.001). BRS correlated with mean IBI (p < 0.001) in all subjects and also in the particular subgroups, but BRSf was IBI-independent. Results of multiregression equations were BRS = 1.37 - 0.56 x age (years) + 0.02 x IBI (ms) (p < 0.001 for BRS vs. age and for BRS vs. IBI); BRSf = 34.74 - 0.97 x age (years) - 0.001 x IBI (ms) (p < 0.001 only for BRS vs. age), where age was measured in years and IBI was measured in ms. The limits of BRS were estimated for the total group: 5th percentile, 3.9; 50th percentile, 9.1; and 95th percentile, 18.7 ms/mmHg; and limits for BRSf were 5th percentile, 8.5; 50th percentile, 16.4; and 95th percentile, 33.6 mHz/mmHg. We conclude that IBI-dependent BRS was unchanged in the particular age groups, but the standardization of BRS on IBI decreased with age. BRSf was IBI-independent and better reflected the development of the BRS.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".